Voice conversion using partitions of spectral feature space

Given a set of utterances that have been spoken by two speakers, the problem of voice conversion consists in constructing some sort of transformation that can be applied on any utterance of the first speaker and makes the result appear to have been spoken by the second speaker. Conversion rules for the vocal tract spectral characteristics, which are usually trained on individual subsets of a partition of the spectral feature space, still do not reach the desired level of accuracy. The paper presents an analysis of the problem.